Breast Cancer, Breast Lesions, Breast Mass
Conditions
Keywords
Breast cancer, Breast Imaging
Brief summary
This study evaluates a second review of ultrasound images of breast lesions using an interactive deep learning (or artificial intelligence) program developed by Samsung Medical Imaging, to see if this artificial intelligence will help the Radiologist make more accurate diagnoses.
Detailed description
Using ultrasound images prospectively acquired, the purpose of this study entails a second review of ultrasound images with suspicious breast lesions using an interactive deep learning (or artificial intelligence) program developed by SamsungMedison Co.,Ltd. The images will be reviewed by the radiologists twice: first without, and then with assistance of artificial intelligence program by SamsungMedison Co., Ltd. BIRADS system will be used in this study. The objectives of the study are twofold: to quantify the statistical equivalence of radiologists' opinion and AI's output (CADe), and to check BIRADS score-based diagnostic accuracy (CADx) that is gained by the Radiologists' use of this interactive tool
Interventions
DEVICEUltrasound Image review with CADe
This software is a computer-aided detection (CADe) software application, designed to assist radiologist to analyze breast ultrasound images. S-Detect automatically segments and classifies shape, orientation, margin, lesion boundary, echo pattern, and posterior feature characteristics of user-selected region of interest. The device uses deep learning methods to perform tissue segmentation and classification of images.
DEVICEUltrasound Image review with CADx
This software is also a computer-assisted diagnostic(CADx) software application, designed to assist a medical doctor in determining diagnosis by presenting whether a lesion is malignant in a breast ultrasound image obtained from an ultrasound imaging device.
DEVICEUltrasound Image manual review
The images will be reviewed by the radiologists using BIRADS scheme without any assistance of artificial assistance. This review will be done off-line using a separate program in entirely manual mode. During this review, BIRADS descriptor choices by each radiologist and the time it takes for the radiologist to make such decision will be stored.
PROCEDUREBiopsy
Suspicious lesions found on breast ultrasound are then followed either by ultrasound guided biopsy or ultrasound imaging every 6 months for two years. For those who undergo biopsy, ultrasound provides images which are used to localize the lesion and guide the placement of the biopsy needle. The sample is sent to pathology for diagnosis, while the ultrasound guidance images are stored. For those who have imaging follow-up, ultrasound images of the breast mass are obtained, digitally stored and interpreted by the radiologist typically using BIRADS scheme.
Sponsors
University of Rochester
Samsung Medison
Study design
Allocation
RANDOMIZED
Intervention model
CROSSOVER
Primary purpose
DEVICE_FEASIBILITY
Masking
SINGLE (Outcomes Assessor)
Masking description
The study consisted of 10 readers with varying levels of training and experience providing analysis on a randomized set of 300 patients' breast ultrasound data with and without S-Detect for Breast. Two reading periods separated by at least 3-week washout, totaling 600 cases analyzed per reader. PI and her associate have knowledge about patients diagnosis and other information. So, they are exclueded in readers for reviewing. And all breast US images are de-indentified.
Intervention model description
This clinical study performed by multiple reader multiple case (MRMC) study design, where as set of clinical readers evaulate under multiple reading condition. All Interpreting physician(reader) independently read all of the cases. (fully-crossed design).
Eligibility
Sex/Gender
ALL
Age
19 Years to No maximum
Healthy volunteers
Yes
Inclusion criteria
1. Inclusion Criteria: * Adult females or males recommended for ultrasound-guided breast lesion biopsy or ultrasound follow-up with at least one suspicious lesion * Age \> 18 years * Able to provide informed consent 2.
Exclusion criteria
* Unable to read and understand English * Unable or unwilling to provide informed consent * A patient with current or previous diagnosis of breast cancer in the same quadrant * Unable or unwilling to undergo study procedures 3. Subject Characteristics 1. Number of Subjects: 300 subjects from 300 separate breast lesions can be acquired. If a subject has more than 1 suspicious lesion, each may be chosen by the radiologist attending as suitable for second review. 2. Gender and Age of Subjects: Adult females or males aged 18 years or older who meet all of the inclusion criteria and none of the
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Concordance rate | 2 days | Breast Imaging Reporting and Data System descriptors suggested by S-Detect for Breast are in good agreement with those selected by experts. In other words, the Breast Imaging Reporting and Data System Lexicon values generated by S-Detect for Breast are not statistically different from the consensus of experts. Breast Imaging Reporting and Data System Assessment Category Score: The user makes the final decision on the Assessment Category Score. Using this Score, S-Detect displays the assessment description. Category 0: Incomplete - Need Additional Imaging Evaluation Category 1: Negative Category 2: Benign Category 3: Probably Benign Category 4a: Low suspicion for malignancy Category 4b: Moderate suspicion for malignancy Category 4c: High suspicion for Malignancy Category 5: Highly Suggestive of Malignancy Category 6: Known Biopsy-Proven Malignancy |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Consensus | 2 day | Evaluate the consensus between manually reading of Breast Imaging without assistance and Automatically detection results(Breast Imaging Reporting and Data System Lexicons). Average of consensus is evaluated in both of Expert group and non-expert group. |
| Accuracy | 7 day | Comparing to the Breast Biopsy results, The accuracy of Breast Imaging results by radiologists with CADx will be evaluated. |
| Reporting time | 2 day | Measure reporting time of Breast Imaging Reporting and Data System Lexicon value in Breast imaging by radiologists without S-Detect for Breast and also measured report time by radiologists with S-Detect for Breast. |
| Specificity | 7 day | Comparing to the Breast Biopsy results, The specificity of Breast Imaging results by radiologists with CADx will be evaluated. |
| Area Under Curve | 7 day | Comparing to the Breast Biopsy results, Area Under Curve (ROC analysis) of Breast Imaging results by radiologists with CADx will be evaluated. |
| Sensitivity | 7 day | Comparing to the Breast Biopsy results, The sensitivity of Breast Imaging results by radiologists with CADx will be evaluated. |
Countries
United States
Outcome results
None listed